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04/15/2023
Learning in latent spaces improves the predictive accuracy of deep neural operators
Operator regression provides a powerful means of constructing discretiza...
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04/20/2022
Deep transfer learning for partial differential equations under conditional shift with DeepONet
Traditional machine learning algorithms are designed to learn in isolati...
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03/09/2022
On the influence of over-parameterization in manifold based surrogates and deep neural operators
Constructing accurate and generalizable approximators for complex physic...
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02/09/2022
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems
Constructing surrogate models for uncertainty quantification (UQ) on com...
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09/28/2021
Grassmannian diffusion maps based surrogate modeling via geometric harmonics
In this paper, a novel surrogate model based on the Grassmannian diffusi...
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08/17/2021
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra
Constructing probability densities for inference in high-dimensional spe...
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07/21/2021